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Related Concept Videos

X-ray Crystallography02:18

X-ray Crystallography

The size of the unit cell and the arrangement of atoms in a crystal may be determined from measurements of the diffraction of X-rays by the crystal, termed X-ray crystallography.
Diffraction
Diffraction is the change in the direction of travel experienced by an electromagnetic wave when it encounters a physical barrier whose dimensions are comparable to those of the wavelength of the light. X-rays are electromagnetic radiation with wavelengths about as long as the distance between neighboring...
Interference and Diffraction02:18

Interference and Diffraction

Interference is a characteristic phenomenon exhibited by waves. When two electromagnetic waves interact with their peaks and troughs coinciding, a resulting wave with enhanced amplitude is produced. This is known as constructive interference. In this case, the two waves interacting are in phase with each other.
X-ray Diffraction of Biological Samples01:10

X-ray Diffraction of Biological Samples

X-ray diffraction or XRD is an analytical tool that utilizes X-rays to study ordered structures such as crystalline organic and inorganic samples, polycrystalline materials, proteins, carbohydrates, and drugs.
According to Bragg's law, when X-rays strike the sample positioned on a stage, the rays are  scattered by the electron clouds around the sample atoms. The  X-ray diffraction or scattering is caused by constructive interference of the X-ray waves that reflect off the internal crystal...
Determination of Crystal Structures01:29

Determination of Crystal Structures

In the late 1800s, the revelation that light extended beyond visible wavelengths led to the discovery of X-rays by Wilhelm Roentgen. Recognized as high-energy electromagnetic radiation with short wavelengths, X-rays prompted exploration into their interaction with crystals. Max von Laue proposed in 1912 that the periodic arrangement of atoms, ions, or molecules in crystals would cause them to diffract X-rays, a hypothesis confirmed through experiments with copper sulfate and zinc sulfide...

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Related Experiment Video

Updated: May 9, 2026

Microfluidic Dry-spinning and Characterization of Regenerated Silk Fibroin Fibers
08:28

Microfluidic Dry-spinning and Characterization of Regenerated Silk Fibroin Fibers

Published on: September 4, 2017

Fiber diffraction without fibers.

H-C Poon1, P Schwander, M Uddin

  • 1Department of Physics, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin 53211, USA.

Physical Review Letters
|July 16, 2013
PubMed
Summary
This summary is machine-generated.

Computational postprocessing of X-ray diffraction patterns from randomly oriented helical particles can simulate fiber diffraction. This enables single-axis alignment computationally, simplifying structural analysis without experimental fiber formation.

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Disentangling High Strength Copolymer Aramid Fibers to Enable the Determination of Their Mechanical Properties
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Disentangling High Strength Copolymer Aramid Fibers to Enable the Determination of Their Mechanical Properties

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Last Updated: May 9, 2026

Microfluidic Dry-spinning and Characterization of Regenerated Silk Fibroin Fibers
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Microfluidic Dry-spinning and Characterization of Regenerated Silk Fibroin Fibers

Published on: September 4, 2017

Disentangling High Strength Copolymer Aramid Fibers to Enable the Determination of Their Mechanical Properties
06:02

Disentangling High Strength Copolymer Aramid Fibers to Enable the Determination of Their Mechanical Properties

Published on: September 1, 2018

Area of Science:

  • Structural biology
  • X-ray crystallography
  • Biophysics

Background:

  • Helical particles are common in biological systems.
  • Determining the structure of randomly oriented particles is challenging.
  • Current methods for particle alignment are often experimentally intensive.

Purpose of the Study:

  • To develop a computational method for analyzing diffraction data from randomly oriented helical particles.
  • To enable single-axis alignment computationally, mimicking fiber diffraction.
  • To facilitate structural determination without physical sample manipulation.

Main Methods:

  • Postprocessing of diffraction patterns obtained from 'diffract-and-destroy' experiments using X-ray free electron lasers.
  • Simulating fiber diffraction patterns from randomly oriented helical particle data.
  • Applying computational single-axis alignment techniques.

Main Results:

  • Successfully generated fiber diffraction patterns from randomly oriented helical particle data.
  • Demonstrated the feasibility of computational single-axis alignment.
  • Validated the approach for subsequent structural analysis.

Conclusions:

  • Computational postprocessing offers a viable alternative to experimental alignment for helical particles.
  • This method simplifies structural determination, particularly for challenging samples.
  • Enables structure elucidation through iterative phasing or standard fiber diffraction methods.